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Modelling tools for the survival of the NHS

A light-up red heart and blue NHS sign

The NHS is under the greatest strain of its 75-year history. Increased demand in the wake of the COVID pandemic, hitting at a time of record staff shortages and high costs, is threatening this precious national asset and urgent intervention is needed to support healthcare staff. If the NHS is to survive, it needs to increase its resilience with the resources it already has. However, with an organisation so large the scale of this challenge is immense.

“Part of the difficulty is that different units and patient pathways are highly interconnected so any change to one part of the system can have potentially negative effects on other parts,” explains Professor Claudia Eckert, an engineering design researcher at The Open University. “This is illustrated by the problem of getting ambulances to deliver patients to A&E where the patients cannot be discharged into wards because the beds are blocked,” remarks Dr Mark Addis, a philosophy and social science researcher also at The Open University.

With so many different factors at play, establishing safe and efficient changes to the healthcare process is incredibly difficult and often attempts to improve individual elements result in more inefficiency in the overall system. Fortunately, Eckert and her collaborators at the University of Cambridge have a potential solution in hand and, as part of the Open University's Open Societal Challenges programme, are currently developing modelling tools to represent and engage with allocation of resources within healthcare systems. “If we can model the resources of a hospital it will enable NHS stakeholders to analyse where they have spare capacity, which resources they can redeploy, and how strategic investment in new staff or equipment will create buffers which allow them to be more flexible in the future,” comments Eckert.

Using system engineering modelling techniques originally developed for the design of complex mechanical systems, such as aircrafts, the project team hope to develop a comprehensive tool to help NHS managers better understand the capabilities and limitations of their existing resources. The project involves close two-way dialogue and the early stages will see the researchers speaking to staff in the NHS thereby building up a picture not only of current healthcare procedures but also of the specific needs and skill sets of different healthcare workers.

With this people-focused foundation in place, Eckert and collaborators will begin to combine appropriate modelling techniques to address the challenges and knowledge gaps identified across the NHS. One such core approach is change prediction models which show how changes in one area may affect other seemingly unrelated parts of the system and will provide a reliable means to analyse the impacts of resource allocation. Eckert concludes “Our vision is to contribute to the systemic resilience of the NHS by giving NHS decision makers effective modelling tools to understand the complex interconnected systems and how they can be used to give maximum impact”.